Pregled bibliografske jedinice broj: 1076013
The Local Rényi Entropy Based Shrinkage Algorithm for Sparse TFD Reconstruction
The Local Rényi Entropy Based Shrinkage Algorithm for Sparse TFD Reconstruction // International Conference on Broadband Communications for Next Generation Networks and Multimedia Applications (CoBCom)
Graz, Austrija, 2020. str. 108-115 doi:10.1109/CoBCom49975.2020.9174168 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1076013 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
The Local Rényi Entropy Based Shrinkage Algorithm
for Sparse TFD Reconstruction
Autori
Jurdana, Vedran ; Volaric, Ivan ; Sučić, Viktor
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
International Conference on Broadband Communications for Next Generation Networks and Multimedia Applications (CoBCom)
/ - , 2020, 108-115
Skup
International Conference on Broadband Communications for Next Generation Networks and Multimedia Applications (CoBCom 2020 )
Mjesto i datum
Graz, Austrija, 07.07.2020. - 09.07.2020
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
time-frequency distribution ; short-term Renyi entropy ; narrow-band Renyi entropy ; sparse signal reconstruction
Sažetak
Observing a non-stationary signal with the time and frequency representation being mutually exclusive often does not provide enough information. Thus, the joint time-frequency distribution (TFD) is used as a convenient and powerful tool for analysis of such signals. Although TFD overcomes many signal representation limitations, it also introduces additional challenges. The removal of artefacts, also called the cross-terms, while maintaining a high concentration of the signal components (auto-terms) is the main problem of the time-frequency (TF) signal analysis. Among different approaches of solving this problem, in this paper we are investigating the advantages of the TFD sparsity, that is, the fact that the energy is accumulated around the instantaneous frequency law of the signal components. In this paper, we present a sparse TFD reconstruction algorithm based on the iterative shrinkage algorithm. The shrinkage is performed independently for each TFD time- and frequencyslice by taking advantage obtained from the short-term and the narrow-band R´enyi entropy. Using the TFD concentration measure and reconstruction algorithm execution time, the obtained results have been compared to the state-of-the-art sparse reconstruction algorithms.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika
POVEZANOST RADA
Ustanove:
Tehnički fakultet, Rijeka
